---
schema_version: "1"
id: ecd71de359e4dcde86c86cef62450d6b3907487cdf60f3af78354f2cdcdc8129
title: Connect a SageMaker Model
collection: admin
version: current
locale: en-us
portal_url: https://docs.salesforce.com/admin/current/en-us/data/264-0-0/c360_a_connect_your_external_model.md
canonical_url: https://help.salesforce.com/s/articleView?id=data.c360_a_connect_your_external_model.htm&release=264.0.0&type=5
source_site: help.salesforce.com
content_type: documentation
content_hash: 95a893e5120e3f29765c175f05f8a00f28cbcded58ba513def9dba63e48fd55e
description: To consume your predictions in Salesforce, connect your SageMaker model with Data 360 and define the prediction criteria for your use case.
products:
  - Data 360
release: "264"
---
# Connect a SageMaker Model

To consume your predictions in Salesforce, connect your SageMaker model with Data 360 and define the prediction criteria for your use case.

### Required Editions

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small edition"><colgroup><col></colgroup><tbody><tr class=""><td class="slds-cell-wrap" style="vertical-align:top;">Available in: <strong>All Editions</strong> supported by Data 360. See <a href="https://help.salesforce.com/s/articleView?id=data.c360_a_dc_editions.htm&amp;language=en_US" target="_blank">Data 360 edition availability</a>.</td></tr></tbody></table>

<table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small permission">
        <colgroup>
          <col style="width:50%">
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          <tr class="">
            <th scope="colgroup" class="slds-cell-wrap" colspan="2" style="text-align:center;vertical-align:top;" id="d217755e58">USER PERMISSIONS
              NEEDED</th>
          </tr>
        </thead>
        <tbody>
          <tr class="">
            <td data-label="USER PERMISSIONS NEEDED" class="slds-cell-wrap" style="vertical-align:top;" headers="d217755e58 ">Allow users to manage models in AI Models</td>

            <td class="slds-cell-wrap" style="vertical-align:top;" headers="d217755e58 ">Enables you to create, update, and delete models in AI Models.</td>

          </tr>
        </tbody>
      </table> <table class="slds-table slds-table_bordered slds-max-medium-table_stacked slds-m-bottom_small permission">
        <colgroup>
          <col style="width:50%">
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        <thead class="slds-text-title_caps ">
          <tr class="">
            <th scope="colgroup" class="slds-cell-wrap" colspan="2" style="text-align:center;vertical-align:top;" id="d217755e88">PERMISSION SETS </th>
          </tr>
        </thead>
        <tbody>
          <tr class="">
            <td data-label="PERMISSION SETS" class="slds-cell-wrap" style="vertical-align:top;" headers="d217755e88 ">Data Cloud Architect</td>

            <td class="slds-cell-wrap" style="vertical-align:top;" headers="d217755e88 ">Admin-level access to all AI Models features, including the ability to create,
              update, delete, and activate models.</td>

          </tr>
          <tr class="">
            <td data-label="PERMISSION SETS" class="slds-cell-wrap" style="vertical-align:top;" headers="d217755e88 ">Data Cloud User</td>

            <td class="slds-cell-wrap" style="vertical-align:top;" headers="d217755e88 ">Restricted access to use a model, including getting predictions and
              improvements derived from a model.</td>

          </tr>
        </tbody>
      </table>

1. In AI Models (formerly Einstein Studio), on the Predictive tab, click **Add Predictive Model**.
    
    ![Model Builder view with the Predictive tab.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/data_cloud/images/c360_a_ai_byom_connect_amazon_sagemaker_model_predictive.png)
2. To choose your model type, click **Connect an Amazon SageMaker model**. Then click **Next**.
    
    ![Model Builder with a view of the SageMaker model type.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/data_cloud/images/c360_a_ai_byom_connect_amazon_sagemaker_model_choose_type.png)
3. To connect the endpoint and access your model inferences, specify these details. Then click **Next**.
    
    ![Model Builder page that enables you to define various SageMaker endpoint parameters.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/data_cloud/images/c360_a_ai_byom_connect_amazon_sagemaker_model_endpoint.jpg)
    
    - Name—Endpoint name
    - URL—Endpoint URL
    - Authentication—Key based or JWT (API gateway required for both)
    - Audience—Alphanumeric string or combination for JWT authentication.
    - Auth Header—Authorization header
    - Secret Key—Alphanumeric string or combination.
    - Request Format—Format for requesting data from the application or server.
        - JSON dense
        - CSV
    - Response Format—Format for providing data from a server response.
        - JSON
        - CSV
4. To add schema, click **Enter the inputs and outputs**.
    
    ![Model Builder view that displays your model schema. You add your inputs and outputs here.](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/data_cloud/images/c360_a_ai_byom_connect_model_builder_schema.png)
    
    1. To add inputs (variables) that can impact your prediction, click **Add Input**. Then specify a name, an API name, and select the data type. Save your work as you add the inputs.
    2. To add your outputs, click **Add Output**. Then specify a name, an API name, a data type, and the JSON Key in a format similar to “$.predictions”. Save your work as you add the outputs.
        
        ![Important](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/images/icon_important.png)
        
        Important You must position the inputs in the order that matches your SageMaker Select Query. To move an input, drag it to the preferred position in the Inputs section.
5. Click **Next**.
6. Review your model settings. Then save your work.
7. To update your settings, click the section where you want to make changes. Then navigate through the flow to review all your settings.
8. If you're satisfied, click **Save**.
9. Name your model. Then click **Save & Connect**. After the model is connected, you can find it on the models list view, Predictive Models tab.
10. To view your model details, click the model. You can activate, edit, or delete a model on this page.
11. After the model is activated, go to the Usage tab. Here you can create prediction jobs that enable you to consume predictions from the model.
12. If you created a batch prediction, click **Run** to refresh your prediction scores.
    
    ![Note](https://sf-zdocs-cdn-prod.zoominsoftware.com/tdta-data-data_cloud-264-0-0-production-enus/f3569962-3c9b-4f83-9d0c-b6a574e785da/images/icon_note.png)
    
    Note With streaming predictions, new inferences are initiated only when there’s a change in the input on your Data Model Object (DMO).

#### See Also

- [_External_: Bring your Own AI Models to Data Cloud](https://developer.salesforce.com/blogs/2023/08/bring-your-own-ai-models-to-salesforce-with-einstein-studio)
- [_Salesforce Help_: Get Predictions From Your Model](https://help.salesforce.com/s/articleView?id=data.c360_a_get_predictions_from_your_model.htm&release=264.0.0&type=5 "There are many ways in which you can consume predictions, prescriptions, and top factors returned from predictive models.")